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Record W2006066779 · doi:10.2118/152200-ms

Prediction And Optimization Of Fracturing In Tight Gas And Shale Using A Coupled Geomechanical Model Of Combined Tensile And Shear Fracturing

2012· article· en· W2006066779 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Hydraulic Fracturing Technology Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTight gasHydraulic fracturingGeomechanicsGeologyShear (geology)Oil shalePetroleum engineeringMicroseismUnconventional oilPermeability (electromagnetism)Ultimate tensile strengthShale gasGeotechnical engineeringMaterials sciencePetrologyComposite materialSeismology

Abstract

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Abstract Hydraulic fracturing is a stimulation technique essential for economical development of tight gas and shale gas reservoirs. Analysis of the performance of fracturing jobs and optimization of the treatment design requires modeling which accounts for all important features of the process and ideally covers both the treatment and post-stimulation production of the well. It is now well established that the productivity of the wells is due not only to the classical tensile single plane fracture (SPF), but to the development of an enhanced permeability region (stimulated reservoir volume or SRV) around it due to shear fracturing and/or stimulation of existing dual porosity. The shape and size of the SRV depends not only on the injection process but also on the geomechanics of the reservoir. Current techniques are not able to predict its dependence on frac job parameters, which precludes any meaningful optimization. Typically the SRV size is assumed (e.g., from microseismic) in production forecasting. In this work we have developed a new coupled geomechanical and flow model for analysis and optimization of tight and shale gas treatments. The formulation includes the propagation of a tensile (SPF) fracture and dynamic development of the shear failure. Non-fractured blocks are assumed to be of linear elastic material; whereas in the failed blocks, fractures and rock compliance matrices are homogenized to form an equivalent compliance matrix. Simple Mohr-Coulomb and tensile failure relationships were used as the criteria for detecting fracture creation. Hyperbolic functions are used to describe the fracture normal and pre-peak shear deformations while the post-peak shear behavior follows an elasto-plastic model. The permeability enhancement during the fracturing process is computed and is the principal coupling between the flow and geomechanics. The model is 3-dimensional and treats both normal and shear behaviour of fractures. The simulation results reveal that shear fracturing will be the dominant fracturing mechanism in cases where the rock cohesion is low and the deviatoric stress is high, whereas tensile fracturing prevails in other conditions. The new model will be a realistic tool for analyzing the dependence of the well productivity on design parameters such as stage volume and pumping rate, spacing between stages, etc. It can be also used to screen shale plays for the most favorable geomechanical conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.215
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it